Layout optimization of irregular storage areas under class storage strategy based on clustering and multi-bin size packing problem

This paper proposes an optimization scheme for the layout of irregular warehouse spaces based on a class-based storage strategy. Firstly, we transform the irregular warehouse space into several regular rectangular areas. Next, through the class-based storage strategy, we develop an algorithm that converts the non-linear clustering problem of homogeneous shelves into a linear selection problem of different sized regular shelf areas. Finally, a comprehensive shelving clustering algorithm and packing problem with different box sizes selection were constructed, and empirical analysis was conducted based on actual data from Xiangtai Warehouse of State Grid Corporation of China. The results show that the new model not only effectively solves the irregular warehouse layout optimization problem under the class storage strategy but also reduces the complexity of the model and shortens the solution time. It is a universally applicable method with significant value for generalization.

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Publication Details

Journal
PLoS ONE
Published
2024-08-30
DOI
https://doi.org/10.1371/journal.pone.0307218
Citations
3
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
1.05

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article

Layout optimization of irregular storage areas under class storage strategy based on clustering and multi-bin size packing problem

Wenbin Zhang, Yiming Wang, Ronghua Zhang, Yuejun Jin
3 citations
PLoS ONE
Advanced Manufacturing and Logistics Optimization
1.05
article

Layout optimization of irregular storage areas under class storage strategy based on clustering and multi-bin size packing problem

Wenbin Zhang, Yiming Wang, Ronghua Zhang, Yuejun Jin
article en
3 citations

Abstract

This paper proposes an optimization scheme for the layout of irregular warehouse spaces based on a class-based storage strategy. Firstly, we transform the irregular warehouse space into several regular rectangular areas. Next, through the class-based storage strategy, we develop an algorithm that converts the non-linear clustering problem of homogeneous shelves into a linear selection problem of different sized regular shelf areas. Finally, a comprehensive shelving clustering algorithm and packing problem with different box sizes selection were constructed, and empirical analysis was conducted based on actual data from Xiangtai Warehouse of State Grid Corporation of China. The results show that the new model not only effectively solves the irregular warehouse layout optimization problem under the class storage strategy but also reduces the complexity of the model and shortens the solution time. It is a universally applicable method with significant value for generalization.

PLoS ONEVol. 19(8)
Jiangsu Second Normal University (CN)
State Grid Corporation of China, Science and Technology Foundation of State Grid Corporation of China
Openalex Percentile: Top 20%
Advanced Manufacturing and Logistics Optimization
1.05
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